Top Machine Learning Jobs in Calgary

The Senior Manager of AI/ML Infrastructure will lead a team to develop and manage cloud-native AI/ML infrastructure, focusing on both Generative and traditional AI/ML technologies. Responsibilities include overseeing the AI/ML model lifecycle, ensuring robust architecture, and collaborating with various teams to align infrastructure needs with business goals. The role emphasizes technical leadership and strategic development in a rapidly evolving technological environment.

The AI Machine Learning Engineer will develop the next generation of personalized user experiences by building effective data and models, particularly focusing on LLM and DNN architectures, to deliver scalable solutions and collaborate with product teams.

As a Machine Learning Engineer focusing on Robot Perception, you will develop and deploy algorithmic solutions for object detection and scene understanding. This role includes optimizing perception pipelines, integrating sensor data, and collaborating with hardware engineers to enhance robotic capabilities.

As a Machine Learning Engineer at Altos Labs, you will develop scalable systems for multi-modal generative foundation models, focusing on training large-scale ML systems with multimodal data and automating analytical pipelines. Collaboration with other scientists and engineers is key in this fast-paced environment, emphasizing teamwork and scientific integrity.

As a Software Engineer, you will design and implement tools and pipelines for AI autonomy systems, working with large datasets and collaborating with scientists and engineers.

The role involves designing and implementing infrastructure for training and deploying deep learning models in self-driving trucks, optimizing performance, and collaborating across teams.

Work with product managers to enhance ML workflows and tools. Drive improvements in DVC's entry point and optimize ML practices.

The AI/ML Specialist Solutions Architect will design scalable AI solutions, build customer relationships, deliver technical presentations, and collaborate with engineering teams to prioritize feedback.

As a Senior Machine Learning Engineer, you'll bridge the gap between data science and ad systems engineering, developing solutions for model experimentation, monitoring, and pipelines, while driving innovation and best practices in machine learning systems.

The Machine Learning Engineer will develop machine learning solutions to enhance data activation products, focusing on personalization, automated experimentation, predictive modeling, content generation, and budget optimization. Responsibilities include customer research, predictive modeling, and working with machine learning infrastructure in a remote-first environment.

As a Software Engineer, you will develop end-to-end data analytics and MLOps solutions using open-source tools, collaborate with a distributed team, debug issues, and maintain cloud-deployed solutions for public and private infrastructures.

As the Director of Engineering for Machine Learning, you'll lead multiple teams to advance deep learning applications in robotics, manage large teams, and develop collaborative relationships to drive technical vision in autonomous driving.